NEW - YOLOv8 🚀 in PyTorch > ONNX > OpenVINO > CoreML > TFLite

Short, concise yet complete implementations of various Yolo models in the style of Tinygrad, but in pure Pytorch.

High-performance multiple object tracking based on YOLO, Deep SORT, and KLT 🚀

YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite

YOLOv3 in PyTorch > ONNX > CoreML > TFLite

YAYA - Yet annother YOLO annoter for images (in QT5). Support yolo format, image modifications, labeling and detecting with previously trained detector.

👁️ OmniView is an advanced video viewing and recording application that offers a range of features including real-time object detection and screenshot capturing. This project uses the OpenCV library for camera connection and video processing, ensuring smooth and high-quality video streams

3rd try

This repository tackles traffic congestion in smart cities using computer vision. The system automatically detects and classifies vehicles, analyzes traffic density, and dynamically adjusts traffic lights - all to optimize traffic flow!

detect license plate and read text on it

YOLOv4 / Scaled-YOLOv4 / YOLO - Neural Networks for Object Detection (Windows and Linux version of Darknet )

Object Detection toolkit based on PaddlePaddle. It supports object detection, instance segmentation, multiple object tracking and real-time multi-person keypoint detection.

YOLOX is a high-performance anchor-free YOLO, exceeding yolov3~v5 with MegEngine, ONNX, TensorRT, ncnn, and OpenVINO supported. Documentation: https://yolox.readthedocs.io/

NVIDIA DeepStream SDK 7.0 / 6.4 / 6.3 / 6.2 / 6.1.1 / 6.1 / 6.0.1 / 6.0 / 5.1 implementation for YOLO models

🚀 TensorRT-YOLO: Supports YOLOv3, YOLOv5, YOLOv6, YOLOv7, YOLOv8, YOLOv9, YOLOv10, and PP-YOLOE using TensorRT acceleration with EfficientNMS, CUDA Kernels and CUDA Graphs!

Implementation of paper - YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors

YOLOv4 - Neural Networks for Object Detection (Windows and Linux version of Darknet )

TensorRT MODNet, YOLOv4, YOLOv3, SSD, MTCNN, and GoogLeNet

Python program that classifies playing cards on a live video feed. Dataset is generated synthetically.

NSL3130AA, OpenCV, Point Cloud, Deep Learning, YOLOv3, SSD-MobilenetV2